Borehole imaging tools provide different types of borehole images, for example, electrical tools like the Formation MicroImager (FMI) tool, Resistivity At Bit (RAB) and Azimuthal Laterolog (AzLL) deliver signals that are processed and rendered visible, by photographic or other print out, or by cathode-ray tube display as a two-dimensional visible image is formed over logged segments of the borehole walls. Likewise, acoustic tools like the Ultrasonic Imaging Tool (USIT) deliver acoustic images of the borehole wall.
In such images, variations of the borehole wall caused for example by geological bed boundaries, fractures or vugs can be visually identified from sharp visible contrasts in the images, which reflect sharp changes in the formation property (e.g. resistivity) at boundaries of the beds. The images thus obtained may exhibit a resolution on the order of 0.5 cm, allowing very fine details of the formation to be distinguished due to the number of sensors in the circumferential direction, and the high rate of sampling in the longitudinal direction.
A key objective of borehole image processing is to geometrically characterize bed boundaries and fractures. When planar events (for example bed boundaries, shistosity, structures such as stilolites, faults or fractures) intersect a borehole, and are inclined or “dipping” at some angle relative to the axis of the borehole, the intersection with the borehole is an ellipse that is represented on the borehole image as a sinusoid since the borehole image is unrolled.
Extracting the dip events—and defining them in terms of sinusoids completely specified by amplitude and phases—might however be a quite tedious and automated dip picking form borehole images is indeed a highly desirable features for most geologists and geophysicist/interpreters. Dip event detection are currently performed using two kinds of applications: one-button application where the detection of dip events is fully automated for the whole depth range of a given borehole image and interactive tools which detect a single dip event with the help of the user.
One-button applications are greatly appreciated by the operators and provide high productivity. One of such applications is known from U.S. Pat. No. 5,162,994 issued Nov. 10, 1992 according to which the borehole image data is interpreted using Hough transforms. Reference is also made to U.S. Pat. No. 5,960,371 issued Sep. 28, 1999. This patent teaches use of the Hough transform to extract dip and azimuth of multiple fractures and beddings from any type of borehole image with respect to a terrestrial reference. The method is robust enough to account for noise or gaps in the images and can separate dips and azimuths of fractures from those of formations. Thus, it can detect and characterize other geometric features (e.g., linear, circular, or ellipsoidal shapes, some of which may represent vugs in carbonate reservoirs) present in the images. However, this method requires huge computation means and times.
This requirement, and the fact that most of the algorithms used for one-button application are based on parameter settings that strongly depend on the type of borehole image and/or are only suitable for a limited range of depth, explain that the one-bottom application are not widely accepted by the experts' community.
Most of the dips picking interactive tools allow users to draw and adjust a sinusoid according to the borehole image. Others, such as the software application known as “BorView”, let the user pick one or several seeds from an image and then compute the sinusoid that fit to the picks. Since users are highly trained professionals, the confidence in the results is high. However, borehole image data include a multitude of such dip events so that the aforementioned manual operations have to be repeated thousand times, obviously a tedious and time-consuming operation. Hence the need for a more user-friendly method.
The present invention seeks at providing means for an improved detection of dip events.